Data driven approach towards disruptive technologies : proceedings of MIDAS 2020 / T.P. Singh, Ravi Tomar, Tanupriya Choudhury, Thinagaran Perumal, Hussain Falih Mahdi, editors.

This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications, organized by the School of Computer Science, University of Petroleum & Energy Studies, Dehradun, India, during 4-5 September 2020. The book addresse...

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Bibliographic Details
Corporate Author: International Conference on Machine Intelligence and Data Science Applications Dehra Dūn, India
Other Authors: Singh, T. P. (Editor), Tomar, Ravi (Editor), Choudhury, Tanupriya (Editor), Perumal, Thinagaran (Editor), Mahdi, Hussain Falih (Editor)
Format: eBook
Language:English
Published: Singapore : Springer, [2021]
Series:Studies in autonomic, data-driven and industrial computing.
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Online Access:Click for online access
Description
Summary:This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications, organized by the School of Computer Science, University of Petroleum & Energy Studies, Dehradun, India, during 4-5 September 2020. The book addresses the algorithmic aspect of machine intelligence which includes the framework and optimization of various states of algorithms. Variety of papers related to wide applications in various fields like data-driven industrial IoT, bioinformatics, network and security, autonomous computing and various other aligned areas. The book concludes with interdisciplinary applications like legal, health care, smart society, cyber-physical system and smart agriculture. All papers have been carefully reviewed. The book is of interest to computer science engineers, lecturers/researchers in machine intelligence discipline and engineering graduates.
Item Description:International conference proceedings.
Includes author index.
Physical Description:1 online resource (xi, 597 pages)
ISBN:9789811598739
9811598738
ISSN:2730-6437
Source of Description, Etc. Note:Online resource; title from PDF title page (SpringerLink, viewed April 14, 2021).